Simulink Simulation Platform Research Articles

Safety-aware human-lead vehicle platooning by proactively reacting to uncertain human behaving

Human-Lead Cooperative Adaptive Cruise Control (HL-CACC) is regarded as a promising vehicle platooning technology in real-world implementation. By utilizing a Human-driven Vehicle (HV) as the platoon leader, HL-CACC reduces the cost and enhances the reliability of perception and decision-making. However, state-of-the-art HL-CACC technology still has a great limitation on driving safety due to the lack of considering the leading human driver’s uncertain behavior. In this study, a HL-CACC controller is designed based on Stochastic Model Predictive Control (SMPC). It is enabled to predict the driving intention of the leading Connected Human-Driven Vehicle (CHV). The proposed controller has the following features: (i) enhanced perceived safety in oscillating traffic; (ii) guaranteed safety against hard brakes; (iii) computational efficiency for real-time implementation. The proposed controller is evaluated on a PreScan&Simulink simulation platform. Real vehicle trajectory data is collected for the calibration of the simulation. Results reveal that the proposed controller: (i) improves perceived safety by 19.17 % in oscillating traffic; (ii) enhances actual safety by 7.76 % against hard brakes; (iii) is confirmed with string stability. The computation time is approximately 3.2 ms when running on a laptop equipped with an Intel i5-13500H CPU. This indicates the proposed controller is ready for real-time implementation.

Research on the impact of hydrodynamic parameter design deviation on the motion performance of fully actuated AUV

Abstract This study, based on the Simulink simulation platform, investigates the influence of hydrodynamic parameters on the navigation speed of fully actuated Autonomous Underwater Vehicles (AUVs) and conducts a sensitivity analysis of AUV motion performance to different design deviations in hydrodynamic parameters. The results show that the velocity of underwater motion in each direction exponentially decreases as the corresponding viscous drag coefficient increases while being less influenced by viscous drag coefficients in other directions. Additionally, the sensitivity of the viscous drag coefficient to the underwater motion of AUVs is much greater than that of the inertial drag coefficient.

Fuzzy‐PID controller based on improved LFPSO for temperature and humidity control in a CA ripening system

AbstractTemperature and humidity as the key factors affecting the storage and ripening of fruits and vegetables directly determine the quality of fruits and vegetables. In this paper, a temperature and humidity model was constructed based on an integrated device of controlled atmosphere storage and ripening. Aiming at the shortcomings of the temperature and humidity model such as large inertia, nonlinearity, and model uncertainty, a fuzzy‐PID controller based on the improved Lévy flight particle swarm algorithm (LFPSO) is proposed. Initially, a mathematical model of temperature and humidity is developed through mechanism research and parameter estimation. Subsequently, a temperature and humidity fuzzy‐PID control strategy is proposed for regulating temperature and humidity. An improved LFPSO is then introduced to optimize the key parameters of the fuzzy‐PID controller, such as the quantization factor and the scale factor. The superiority of the improved LFPSO algorithm is verified by comparing the test functions. Finally, the improved LFPSO‐fuzzy‐PID controller, fuzzy‐PID controller, and Smith‐PID controller are applied to the simulation model for comparison using the MATLAB Simulink simulation platform. The results show that the improved LFPSO‐fuzzy‐PID control algorithm has a good control effect in the temperature and humidity simulation system of controlled atmosphere (CA) ripening container, which provides a reference for solving the optimization problem of actual engineering design.Practical applicationsIn order to reduce the postharvest cold chain losses of fruits and vegetables, this paper proposes a containerized style device that combines fruits and vegetables storage and ripening for simplifying the losses caused by transshipment at cold chain nodes. Since temperature and humidity play a key role in fruits and vegetables storage and ripening, which directly affect the product quality, this paper establishes a complete mathematical model of CA ripening temperature and humidity system by combining mechanism modeling and parameter identification. In order to keep the temperature and humidity within the ideal range, Smith‐PID controller, fuzzy‐PID controller, and fuzzy‐PID control method based on improved Lévy flight particle swarm optimization are proposed to regulate the air conditioner and humidifier. The performance of three different types of controllers was tested on the MATLAB. The simulation results demonstrate that the improved LFPSO‐fuzzy‐PID controller is superior and more effective than Smith‐PID and fuzzy‐PID controllers.

Compensation characterization of the UPQC system under an improved nonlinear controller based on the MSTOGI-PLL device

To solve the delay problem of a unified power quality conditioner (UPQC) system during the separation of the fundamental positive-order components and to better filter out the DC and harmonic components to realize accurate phase locking, a mixed second- and third-order generalized integrator phase-locked loop (MSTOGI-PLL) has been designed to replace the traditional synchronous reference frame phase-locked loop (SRF-PLL). Under the premise of adopting the new phase-locking device of MSTOGI-PLL, the active disturbance rejection control (ADRC) controller or the super-twisting algorithm (STA) sliding mode controller is used in the DC voltage control module instead of the traditional PI controller, and the suitability of the two nonlinear controllers with the MSTOGI-PLL device is investigated. First, the new MSTOGI-PLL device is designed, and the new phase-locking method is applied to make the UPQC realize accurate phase locking under the non-ideal situation of the grid voltage containing unbalance, DC component, harmonics, and so on. Based on the above foundation, the ADRC or STA controller is independently adopted to replace the PI controller to construct the UPQC system with the ADRC + MSTOGI phase-locking device and the second-order STA + MSTOGI phase-locking device. Finally, a simulation comparison is carried out in a Simulink simulation platform regarding the UPQC system under different phase-locking devices, and the simulation results demonstrate that MSTOGI-PLL can successfully filter out the DC component and resolve the phase-locking process delay issue. Additionally, the UPQC system with ADRC + MSTOGI-PLL exhibits superior immunity and response speed to the PI controller and the second-order STA controller.

Model Predictive Control for Trajectory Planning Considering Constraints on Vertical Load Variation

To address the issue of centrifugal force affecting the vertical load during the stability and trajectory planning of autonomous vehicles during high-speed cornering and obstacle avoidance, a model predictive control of trajectory planning and tracking is proposed that considers the roll factor using only a two-degrees-of-freedom vehicle dynamics model. Firstly, a trajectory planning controller is designed. As a predictive model, a dual-track two-degrees-of-freedom vehicle dynamics model is established. This model describes the relationship between tire lateral forces and vertical loads using a quadratic nonlinear tire model. To reflect the actual dynamic state of the vehicle, the controller incorporates a nonlinear constraint that considers vertical load variations. The nonlinear optimization problem is transformed into a simplified quadratic programming problem by using the Jacobian matrix method to linearize the constraints. By fitting a fourth-degree polynomial curve to the discrete points calculated by the replanning algorithm, an optimal collision-free trajectory is obtained. Secondly, an MPC trajectory tracking controller is designed to control the vehicle in real time along the optimal trajectory from the planning, incorporating control quantity constraints, control increment constraints, and lateral angle constraints to maintain the vehicle’s motion state. We transform the trajectory tracking control problem into a quadratic programming problem, solving for the optimal control sequence for the autonomous vehicle to track the trajectory, achieving an optimized solution and rolling time domain control. Finally, the effectiveness of the vehicle’s obstacle avoidance planning and tracking under high-speed double-lane-change maneuver conditions is validated using the Simulink simulation platform. The results indicate that the designed planning and tracking controllers effectively improve the obstacle avoidance planning and tracking control for high-speed autonomous vehicles.

Adaptive MPC-Based Lateral Path-Tracking Control for Automatic Vehicles

Adaptive MPC-Based Lateral Path-Tracking Control for Automatic Vehicles

Assessment Possibilities for Trajectory Fusion of Two Vehicles in the Case of Automated Vehicles

Because of the increasing integration of automation and cutting-edge technology into modern transportation systems, the development of efficient and dependable Automated Vehicles (AVs) has become an important area of research. One of the most important characteristics of AVs is their ability to perceive and navigate complex environments safely. The process of combining trajectory data from multiple vehicles, known as trajectory fusion, has the potential to improve AV perception. The feasibility of implementing trajectory fusion in the context of two autonomous vehicles coexisting in the same operational environment is investigated in this study. The primary goal of this research is to investigate the effectiveness of trajectory fusion in increasing the environmental awareness of Automated Vehicles (AVs), while also investigating its implications for the decision-making mechanisms that govern these vehicles. The MATLAB Simulink simulation platform was essential in carrying out this investigation. The intricate dynamics of trajectory fusion within the context of dual AVs were meticulously analyzed and evaluated using this software.

Image-based visual servoing with Kalman filter and swarm intelligence optimisation algorithm

The article proposes a new Kalman depth estimation and an improved swarm intelligence optimisation algorithm for adaptive tuning of servo gain for image-based visual servo control. First, a Kalman depth estimation model is established from the principle of image-based visual servoing, and two state equations are designed for depth estimation based on the number of state quantities. Second, the improved sparrow search algorithm is proposed to tune the servo gain adaptively to improve the convergence speed and stability. To verify the effectiveness of the proposed method, the conventional image-based visual servoing and conventional Kalman estimation are reproduced and compared with the proposed method, and the simulation is completed on the Simulink simulation platform for verification. Finally, the experiments are completed in the robotic arm experimental platform. Both the simulation and experimental results show the effectiveness of the proposed method, which reduces the redundancy of the camera and shortens the convergence time.

An Energy-Feed Type Split-Capacitor Three-Phase Four-Wire Power Electronic Load Compatible with Various Load Demands

Energy-feed power electronic loads can precisely control the phase and magnitude of the power supply output current, achieving the emulation of loads. Moreover, they can feed energy back to the grid for energy regeneration, demonstrating significant research value. This article proposes an energy-fed power electronic load topology and control method that can realize the static and dynamic simulation of linear and non-linear loads and take into account the simulation needs of single-phase, three-phase three-wire, and three-phase four-wire loads. The main circuit uses a two-stage back-to-back AC/DC/AC structure: the front side is a three-phase four-wire split capacitor PWM rectifier bridge, which is used to simulate loads under various operating conditions; the back side is a three-phase three-wire PWM inverter bridge, which realizes the energy feeding back to the grid and reduces the waste of energy; and the intermediate side uses a split capacitor to equalize the voltage and achieve voltage stabilization. The topology is analyzed under the simulation demands of three-phase balanced, three-phase unbalanced, single-phase and non-linear loads. Finally, a MATLAB(R2022a)/Simulink simulation platform is built for a power electronic load with a rated capacity of 200 kVA. The simulation results verify the effectiveness, feasibility, and advancement of the power electronic load proposed in this article.

基于能耗最优的改进动态窗口法的电动拖拉机避障方法

In order to solve the real-time obstacle avoidance problem in electric tractor operation, an improved dynamic window approach (DWA) based on optimal energy consumption is proposed for electric tractor obstacle avoidance. Firstly, energy consumption model of tractor is established based on the transmission system of electric tractor, then energy consumption evaluation sub-function is introduced to improve the evaluation function of original DWA algorithm, and finally, the trajectory is evaluated and the optimal solution of the trajectory is determined by using new evaluation function. Based on the kinematics model of YL254ET electric tractor in Yancheng Yueda, a model predictive controller is designed. The obstacle avoidance planning and tracking control of electric tractor are simulated jointly on Simulink and CarSim simulation platform. Finally, the obstacle avoidance planning test is carried out. The simulation and experimental results show that after the algorithm improvement, the energy consumption of electric tractors is reduced, the generated path is smoother, and the lateral error is smaller.

Immunity of shunt active power filter based on improved LADRC

To improve the dynamic response speed and performance of active power filter controller, and improve the robustness, tracking ability, and disturbance rejection ability of linear active disturbance rejection controller (ADRC), an improved linear ADRC (LADRC) is proposed. First, a new error adjustment total disturbance is introduced into the linear expansion state observer to adjust the total disturbance of the linear expansion state observer. Then, on the premise of system stability, the controller is applied to the voltage outer loop of shunt active power filter (SAPF), and the mathematical model of active power filter is deduced, and it is controlled according to the first-order linear active disturbance rejection controller. Finally, through frequency domain analysis, the stability, noise immunity, and tracking performance of the improved LADRC are analyzed. Using MATLAB and Simulink simulation platform, the current stability and tracking performance of SAPF under improved LADRC control are simulated and verified, and compared with traditional methods. The simulation results show that the waveform fluctuation of A-phase voltage on the grid side of this method is relatively smooth, and the voltage on the grid side is always kept at ±50 V; the voltage curve of SAPF DC side is kept between the actual set values, about 820 V; the waveform fluctuation of A-phase current on the load side is small, which is ±220 A; the harmonic distortion rate is 4%. It is verified that this method has good tracking effect and anti-interference characteristics, which is of great significance to improve the control performance of active power filter.

LSTM Based 24 hours Ahead Forecasting of Solar PV System for Standalone Household System

A rapid expansion in the technology of solar PV energy in recent years has paved the way for PV market to grow resulting in a cost reduction in material. Hence, technological improvements are eminent to maintain the stable working of the system. In order to create a system many techniques and modules are used like, MPPT algorithms to track the power which increases real-time efficiency, and a battery management system to efficiently manage the stored energy from the battery. This paper aims to design a forecasting model to predict the weather and load of the standalone system to prepare the battery for future use. The forecasting is done using Machine learning and Deep learning tools like RNN, LSTM, and GRU and the results are fed into the system in MATLAB Simulink simulation platform.

Research on Torque Current Error Control of PMSM Based on Model Predictive Control

To solve the problem that the torque pulsation is serious due to the large current error in the period when the duty cycle is calculated by the deadbeat method in the duty cycle dual-vector model predictive current control method, a vector switching method is proposed. The control objective of the proposed method is not to equate the predicted torque current with the reference value under the dead-beat idea, but to reduce the torque current control error by changing the switching time of the voltage vector and ensuring the symmetry of the positive and negative current errors. By deducing the duty cycle, the maximum current errors in a single control cycle before and after vector switching is compared and analyzed. The vector switching method is verified on the Simulink simulation platform and compared with the duty cycle double vector method. The results show that the vector switching method can effectively reduce the intra-cycle torque current tracking error and realize the optimal process control in each cycle.

Electrical and aerodynamic characteristics of sliding discharge based on a microsecond pulsed plasma supply

Plasma flow control technology has broad prospects for application. Compared with conventional dielectric barrier discharge plasma actuators (DBD-PA), the sliding discharge plasma actuator (SD-PA) has the advantages of a large discharge area and a deflectable induced jet. To achieve the basic performance requirements of light weight, low cost, and high reliability required for UAV (Unmanned Aerial Vehicle) plasma flight experiments, this work designed a microsecond pulse plasma supply that can be used for sliding discharge plasma actuators. In this study, the topology of the primary circuit of the microsecond pulse supply is determined, the waveform of the output terminal of the microsecond pulse plasma supply is detected using the Simulink simulation platform, and the design of the actuation voltage, the pulse frequency modulation function and the construction of the hardware circuit are achieved. Using electrical diagnosis and flow field analysis, the actuation characteristics and flow characteristics of sliding discharge plasma under microsecond pulse actuation are studied, the optimal electrical actuation parameters and flow field characteristics are described.

Research on SSTDR-based online distance measurement method for single-phase faults in cables

In order to accurately locate the non-destructive faults of distribution network cables, an extended spectrum time-domain reflectometry method based on the equivalent distribution parameter model of transmission lines was proposed to detect and locate single-phase grounding short-circuit and single-phase disconnection faults online. Firstly, the extended spectrum and time-domain reflectometry are analyzed theoretically. Then through simulink simulation platform to build single-phase grounding and single-phase disconnection fault model of distribution network simulation, verify the correctness of the theory; Finally, the influence of fault distance, fault resistance and signal-to-noise ratio is analyzed.

Control of hybrid electromagnetic bearing and elastic foil gas bearing under deep learning.

The hybrid electromagnetic and elastic foil gas bearing is explored based on the radial basis function (RBF) neural network in this study so as to improve its stabilization in work. The related principles and structure of hybrid electromagnetic and elastic foil gas bearings is introduced firstly. Then, the proportional, integral, and derivative (PID) bearing controller is introduced and improved into two controllers: IPD and CPID. The controllers and hybrid bearing system are controlled based on the RBF neural network based on deep learning. The characteristics of the hybrid bearing system are explored at the end of this study, and the control simulation research is developed based on the Simulink simulation platform. The effects of the PID, IPD, and CIPD controllers based on the RBF neural network are compared, and they are also compared based on the traditional particle swarm optimization (PSO). The results show that the thickness, spread angle, and rotation speed of the elastic foil have great impacts on the bearing system. The proposed CIPD bearing control method based on RBF neural network has the shortest response time and the best control effect. The controller parameter tuning optimization starts to converge after one generation, which is the fastest iteration. It proves that RBF neural network control based on deep learning has high feasibility in hybrid bearing system. Therefore, the results provide an important reference for the application of deep learning in rotating machinery.

A Harmonic Detection Method of UPQC Based on LSL Algorithm in Photovoltaic Microgrids

Photovoltaic microgrids have discontinuity and intermittency issues that affect the load current amplitude and frequency, and this leads to disturbances. The unified power quality conditioner (UPQC) combines a series active power filter (SAPF) and a parallel active power filter (PAPF), and therefore, it has the advantages of SAPF and PAPF to treat power quality problems. Considering detection precision and response speed, and to meet the fast speed and accuracy of PAPF harmonic detection, the algorithm principle of adaptation and least-squares lattice (LSL) is analyzed. A new harmonic detection method of three-phase circuit based on LSL adaptive algorithm is proposed. The two other harmonic detection methods between least mean square and instantaneous power theory based are compared using the Simulink simulation platform. The compensation effect of LSL is more stable and better than the two other methods. The experimental results also indicate that the new method based on LSL can accurately detect and compensate the harmonic component in photovoltaic microgrids in real time. Therefore, this harmonic detection method based on LSL can be used in the practical engineering applications, and it provides a new method for harmonic detection of UPQC PAPF.

Dynamic Analysis and Simulation of Six-Axis Cooperative Robot Based on Screw Theory

In order to realize the precise control of the cooperative robot, it is necessary to establish an accurate dynamic model of the robot. Compared with traditional industrial robots, cooperative robots have joint flexibility effect, so joint flexibility should be taken into account when building dynamic model. In this paper, the six-axis cooperative robot is taken as the research object. The dynamic model of the robot is modeled and analyzed by Newton-Euler method based on screw theory. and the dynamic simulation of the robot is carried out based on Simulink and SimMechanics simulation platform, and the relevant performance curves are obtained. The simulation results verify the validity of the dynamic theoretical model.

Dynamic Coordination Control of HEV Unsteady Operating Mode Switching Based on MPC

Aiming at a hybrid electric vehicle (HEV), the impact problem is studied during the mode switching process under non-steady-state operating conditions. Firstly, the system dynamics model is established, the dynamic characteristics of unsteady conditions are analyzed, the BP neural network engine torque estimation model based on genetic algorithm optimization is established, and the engine torque is estimated online. MG1 torque coordination control and MG2 active compensation control are adopted, a mode switching coordination control strategy based on model prediction is proposed. The MATLAB / Simulink simulation platform is used to verify the effectiveness of the control algorithm. The simulation results show that the coordinated control strategy can effectively achieve the output torque compensation of the drive motor. The engine is actually close to the target torque. Compared with the uncoordinated control, During the speed synchronization phase, the maximum impact of the vehicle was reduced by 60.4%.

Active Power Sharing Method of Battery Energy Storage Systems for Frequency Control of Commercial Park Power Grids

In this paper, a frequency control method for off-grid operation of energy storage systems has been proposed with virtual synchronous control. Firstly, the single-machine mathematical model of the power converter system (PCS) controlled by the virtual synchronous machine is established. Secondly, energy storage systems based on virtual synchronous control have been analyzed. Finally, two battery energy storage systems (BESS) were built on the SIMULINK simulation platform to realize island operation of the energy storage system, which verified the effectiveness of the proposed control strategy.